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Google Security Operations Engineer (Beta) Sample Questions:

1. You are working with your company's analyst team to automate the investigation of phishing alerts ingested directly into Google Security Operations (SecOps) SOAR from an email inbox.
The analyst team currently uses a SIEM query to search for related information. You need to design a solution to automatically include the query results in the Google SecOps case without writing any new code. What should you do?

A) Add an action to the playbook that runs the SIEM query and returns the results.
B) Modify the detection rule in the SIEM to include the query results as part of the detection.
C) Create a custom action in Google SecOps IDE that runs the SIEM query from a playbook through an API call and returns the results.
D) Add a widget to the Default Case View in Google SecOps SOAR that allows the analyst team to query directly from the widget.

2. Your organization uses the curated detection rule set in Google Security Operations (SecOps) for high priority network indicators. You are finding a vast number of false positives coming from your on-premises proxy servers. You need to reduce the number of alerts. What should you do?

A) Configure a rule exclusion for the network.asset.ip field.
B) Configure a rule exclusion for the principal.ip field.
C) Configure a rule exclusion for the target.domain field.
D) Configure a rule exclusion for the target.ip field.

3. You have noticed that a Google Security Operations (SecOps) detection rule that detects excessive network connections is triggering too frequently and creating too many false positive alerts. You want to improve the rule to reduce the noise without reducing the effectiveness of the rule. What change to the detection rule should you implement?

A) Assign a risk score in the YARA-L outcome: section to prioritize alerts more effectively in the alert queue.
B) Add a threshold in the YARA-L condition: section to ensure that the rule only alerts after a certain number of connections.
C) Update the YARA-L events: section to exclude the most common IP addresses involved in the network connection alerts to reduce the number of alerts.
D) Include a 10 minute timeframe for the same source and destination of network connections in the YARA-L match: section to aggregate the alerts.

4. You work at a financial services company. You need to detect in near real-time when a Cloud Run functions service agent modifies the IAM policy of an Artifact Registry repository. You plan to use Security Command Center (SCC). You want to follow the Google-recommended approach.
What should you do?

A) Use Event Threat Detection in SCC with a custom unexpected Cloud API call rule that detects when a specified principal calls a method against a resource.
B) Create a custom Security Health Analytics (SHA) detector that scans Artifact Registry repositories for IAM policy changes. When a change is detected identify the principal that made the change.
C) Configure a Cloud Logging log sink to export all IAM policy changes to BigQuery, and create a custom dashboard in SCC to visualize the data.
D) Implement a Cloud Run function that is triggered by IAM policy changes within the project and sends an alert to SCC using the Security Command Center API.

5. You are building a detection rule in Google Security Operations (SecOps) to alert on requests to potentially malicious domains. You are planning to use the logs from your network detection and response (NDR) solution but you need to reduce noise and narrow the scope of detections. You want to minimize cost and deploy the solution quickly. What should you do?

A) Build a Google SecOps SOAR playbook that enriches domain entities in alerts with VirusTotal information and auto-closes cases when no domains are classified as malicious.
B) Ingest logs from your threat intelligence platform (TIP), and build a multi-event rule that correlates the domains found in your NDR logs with your threat intelligence data.
C) Build a multi-event rule that correlates the domains found in your NDR logs with WHOIS context in the entity graph and sets the risk score based on domain creation time.
D) Ingest logs from a domain monitoring service, and build a multi-event rule that correlates the domains found in your NDR logs with your domain monitoring data.

Solutions: